Clozapine-induced myocarditis and subsequent rechallenge: a narrative literature review and case report.
Bibliographic record
Abstract
Clozapine is an antipsychotic medication that has been proven effective for the management of treatment-resistant schizophrenia (TRS). For some patients, it is the only medication that can improve disease burden and quality of life. Clozapine comes with various potentially serious adverse effects which may dissuade physicians from prescribing it despite its well-documented efficacy. One of these adverse effects is clozapine-induced myocarditis (CIM). Due to these risks, patients who undergo a clozapine rechallenge after CIM require close monitoring. Myocardial damage can be reversible if CIM is promptly identified, and clozapine is discontinued appropriately. The gold-standard for diagnosing myocarditis is an endomyocardial biopsy but there are no clear recommendations for how to use less invasive screening assessments to monitor for CIM during a clozapine rechallenge. This review article aims to increase awareness of CIM and provide guidance on monitoring and management. The accompanying case report presents a proposed strategy, including biomarkers that were used to identify inflammation and cardiac injury which guided the treatment of an adolescent patient who had a successful clozapine rechallenge. Further research is necessary to validate the proposed monitoring protocol and to further advance guidance for clinicians.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".